Advertisement selection and pricing using discounts based on placement

ABSTRACT

An advertising selection and placement system is provided for a social networking system. An advertising selection module identifies candidate advertisements for a user to view along with social networking content. The candidate advertisements can be placed in various slots on the user&#39;s display. The expected value of various arrangements of the candidate advertisements in the slots is determined, and advertisements may be selected and placed to optimize revenue to the system. Each advertisement is evaluated using a discount function that adjusts the price of the advertisement based on its placement.

BACKGROUND

This invention relates generally to online advertising and in particularto selection, placement, and pricing of advertisements in a socialnetworking system.

Advertising systems typically choose advertisements for users using abidding process to select advertisements. Generally, the advertisementwith the highest bid wins the advertising slot and the advertisement isserved in the advertising slot. In some systems, there are severaladvertising slots to be filled together. The individual advertisementsserved in each slot may have a variable size or may otherwise affect theother advertisements filled together.

SUMMARY

A social networking system provides social networking content to a useralong with advertisements. The advertisements on a page are bid on byadvertisers, which provide ad requests that may include advertisementsof varying sizes and associated bids. The advertisements selected for apage are placed on the page in one or more slots on the page, which arein different actual locations depending on the size of the selectedadvertisements. The placement of the winning advertisements isdetermined based at least in part on the bids for the advertisements,where the bids are discounted based on the placement of theadvertisements on the page. In one embodiment, an expected value for theadvertisements is computed using the discounted bids of theadvertisements for various placements, and the expected values may beused to select the advertisements and their placement on the page.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an overview of a social networking system using advertisingselection and placement according to an embodiment.

FIGS. 2A-2C illustrate discount curves for various placements ofadvertisements on a display screen, according to an embodiment.

FIG. 3 is a flow chart of a method of selecting ad placements accordingto an embodiment.

The figures depict various embodiments of the present invention forpurposes of illustration only. One skilled in the art will readilyrecognize from the following discussion that alternative embodiments ofthe structures and methods illustrated herein may be employed withoutdeparting from the principles of the invention described herein.

DETAILED DESCRIPTION

Overview

FIG. 1 is an overview of a social networking system using advertisingselection and placement according to an embodiment. A social networkingsystem 100 provides social networking content and services to users ofthe social networking system 100. Users connect to the social networkingsystem 100 using client devices 110 through a network 130. Users,through the client devices 110, connect with other users of the socialnetwork, share information and content, and manage relationships on thesocial networking system. As users browse content in the socialnetworking system, the users are also presented with advertisinginformation along with the social networking content. Advertisers 120also connect to the social networking system 100 through the network 130and provide information to the social networking system 100 aboutadvertisements to display to users.

The social networking system 100 includes a page composer 101, socialnetwork data 102, an advertisement selection module 103, and anadvertisement database 104 in an embodiment. The social networkingsystem 100 receives requests from client devices 110 and provides socialnetworking content and information in response. The page composer 101 isa module which receives and processes user requests and composes adisplay for the user. The page composer 101 accesses the social networkdata 102 in response to the user request to identify the requestedsocial networking information for the client device 110. In addition toaccessing the social networking data, the page composer 101 alsodetermines a layout and display for the social networking content. Thepage composer 101 provides information to the client device 110according to the capabilities of the client device 110. For example aclient device 110 which accesses the social networking system 100 usingan html interface is provided a page from the page composer 101 which iscompatible with html. Other client devices 110 access the socialnetworking system 100 using a specialized application, and the pagecomposer 101 returns information using formatting for the specializedapplication to display.

In addition to social networking content, the page composer 101 alsoidentifies advertising slots in the display provided to the clientdevice 110. The advertising slots are provided to the advertisementselection module 103 along with information about the user. Theadvertisement selection module 103 identifies and selects advertisementsto place with the social networking content. In addition to selectingadvertisements, the advertisement selection module 103 determines thearrangement of the advertisements in the display. The advertisementselection module 103 accesses advertisement database 104 to identifyadvertisements for placement in advertising slots. The advertisementdatabase 104 includes information about active advertising campaigns byadvertisers. The advertising campaigns include advertising content forat least one advertisement, an advertising bid, and targeting criteriafor the ads. Advertisers 120 communicate with the social networkingsystem 100 to add and remove advertising campaigns to the advertisementdatabase 104.

The advertising campaigns comprise any paid-for or sponsored content orinformation for presentation to the users of the social networkingsystem 100. In addition, the advertising content varies in type and sizeof the advertisement. For example, some advertisements are a banneradvertisement with a graphic for the advertiser, while otheradvertisements comprise textual information about an advertiseraccompanied by relevant social networking content. The relevant socialnetworking content may be static in the advertisement, or may bedynamic, allowing the social networking content to change depending onthe individual the ad is served to or based on content posted by theadvertiser. As such, the various advertising campaigns have varioustypes of advertisements and have different sizes.

The client device 110 can be any computing platform for interacting withthe social networking system 100. The client device 110 receives socialnetworking and advertising content from the social networking system 100and displays the information to the user of the client device 110. Theclient device 110 also receives input from the user and communicates theinput to the social networking system 100. Suitable client devices 110include desktop computers, tablet computers, mobile devices, and otherdevices capable of networked access to the social networking system 100and displaying information to a user.

Variable Ad Display

FIGS. 2A-2C illustrate discount curves for various placements ofadvertisements on a display screen, according to an embodiment. Socialnetwork display 200 is the display provided to the user of the clientdevice. The social networking system 100 provides the composition ofinformation in the social network display 200 and selection of contentto be provided in the social network display 200. The social networkdisplay 200 includes social network information display 210 and severaladvertisements 220, 221, and 222. The social network information display210 provides social networking content in a portion of the socialnetwork display 200, while the advertisements occupy another portion ofthe display. In an embodiment, the advertisements and social networkcontent are intermixed in various portions of the social network display200. For example, the social network display 200 may include severaltypes of feeds in different portions of the page. Each feed may includeadvertising information in the feed along with social networkingcontent.

The advertisements selected for placement on the page are selected fromactive advertising campaigns in the advertisement database 104. Theadvertisement selection module 103 includes a bidding algorithm toselect the individual advertisements to include on social networkdisplay 200. The bidding algorithm can use a generalized second priceauction, a Vickrey-Clarke-Groves (VCG) auction, or other auctionmethodology for selling several like-kind items. For simplicity in thisdisclosure, the selection of advertisements is selected using a cost perimpression or CPM model of advertiser bidding. That is, the advertiserbids an amount relative to the value of the advertiser of an impressionof the user. Other advertising models may be used, for example using acost-per-click (CPC) model or other method of pricing bids. A CPC modelmay be adjusted by a click through rate for the advertising campaign todetermine an expected cost per impression (eCPM) for the advertisement.The advertising selection and bidding process first determines thenumber of slots available for advertisements, and next executes theauction to determine the winning advertisements.

The advertisements 220, 221, and 222 are advertisements provided in thesocial networking display 200 to the user. The advertisements 220, 221,and 222 are a variety of different sizes, as shown. Advertisement 220 isthe largest advertisement, advertisement 221 is a mid-sizedadvertisement, and advertisement 222 is the smallest advertisement ofthese three. Each advertisement is shown to the user on the socialnetwork display 200. The placement of the advertisements within thesocial network display 200 affects the likelihood a user will interactwith an advertisement. Typically, the advertisements near the top of thepage receive the highest interaction, and there is reduced interactionby the user the further down the page the advertisement is located. Inthis example, there are three slots in the display for advertisements.FIGS. 2A-2C illustrate different placements of the three advertisements220-22 in the three advertising slots.

Comparing the advertisement placements in FIGS. 2A-2C, varyingarrangements of the advertisements 220-222 are shown. Since userinteraction varies according to the location an ad is placed on thedisplay, the selection of an advertisement for a slot affects the amountof user interaction for subsequent slots. For example, a smalleradvertisement has a smaller effect than a larger advertisement, becausethe smaller advertisement allows the subsequent ad to be placed higheron the page. A larger ad forces subsequent ads further down the page.This difference is shown by comparing FIG. 2A with FIG. 2B. In FIG. 2A,the larger ad (advertisement 220) is placed in the first slot, causingthe subsequent ad (advertisement 221) to be placed further down thepage. In FIG. 2B, a smaller ad (222) is placed in the first slot,causing the subsequent ad (220) in the second slot to start higher upthe page relative to FIG. 2A. That is, the offset of each subsequentadvertisement from the top of the page is affected by the priorplacement of ads in the display.

Discount Curves

The effect of placement of an ad on its interaction rate with users ismodeled using discount curves 230. A discount curve represents thereduced interaction rate of users and a discount value for eachadvertising slot as a function of the offset of the ad from the top ofthe ad space. FIGS. 2A-2C illustrate discount curves for threeadvertising slots in three different ad placement configurations. Inthese examples, each advertising slot has its own discount curve. Thefirst slot is represented by discount curve 231, the second slot bydiscount curve 232, and the third slot by discount curve 233. As shown,the discount curve generally decreases as the offset from the top of thepage increases. Though the advertisers bid on the slots in thisembodiment as though the slots were equally valuable, each slot's valuevaries according to the interaction rate of the users. A discount isprovided to the actual price an advertiser pays based on the placementof the advertisement in the slots. Each discount curve provides thediscount for each advertisement given its placement on the page.

The offset for an advertisement is determined using the cumulativeheights of the ads before it. The height of an ad may be static andstored by the social networking system 100 with other information aboutthe advertisement, or the height for an advertisement may be dynamic.The height of an advertisement can be determined by the socialnetworking system 100 by calculating the components of the advertisementand determining the height of the portions. For example an advertisementmay include a social recommendation, a statement about a product, and abanner. For some users provided the ad, there may be no socialrecommendation. The advertising height therefore may be determined on auser-by-user basis as the height of the advertisement changes. In otherembodiments, the system provides the advertisement to a user device, andthe user device renders the advertisement and returns the offset orheight of the advertisements to the social networking system 100. Thereturned information can be stored with the ad to indicate the height ofthe advertisement.

The discount curves are calculated over time using user responses toadvertising placement. As the social networking system 100 placesadvertisements on a page of content for display to users, it canmaintain a record of the positive responses provided by users andcorrelate the user responses to the slot and offset of the ad the userresponded to. Using responses from many users, the social networkingsystem 100 can construct discount curves using actual response datareflecting the user likelihood of interacting with an advertisement. Inone embodiment, the same discount curves are used across advertisementsand users. In other embodiments, the discount curves are adjusted orselected individually for the advertisement or the user. For example, ifan advertisement is served a sufficient number of times, a specializeddiscount curve may be calculated using that individual advertisement.Though the discount curves are generally expected to decrease as offsetincreases, since the discount curve is constructed using user responses,the discount curve will reflect actual user response rates, which mayincrease at a particular offset.

Using the discount curves, the system can determine the expected value(EV) of particular arrangements of advertisements on the page. The EVfor an individual advertiser is the advertiser's price result from theauction P, multiplied by the discount value D for a particularplacement. Using the discount curves, the discount value D is a functionof the slot and the offset: D(slot, offset). The EV for the page is thesum of each advertisement's EV for a given ad placement. As the expectedvalue of the page changes according to the ad placement, the systemidentifies an ad placement order to increase the EV of the page.

FIGS. 2A-2C illustrate discounts using three different ad placements forthe three advertisements 220, 221, and 222. Using the discount factorsfor the various placements in conjunction with the pricing result of theauction, the system can determine which advertising placement to choose.As an example, suppose the results of the auction provided Ad 220 wouldpay $1.00, Ad 221 would pay $0.90, and Ad 222 would pay $0.80. Theactual benefit expected by the advertisers is modified by the placementof the advertisements on the display. As such, the expected value ismodified by the associated discount on the discount curve. Table 1illustrates the value of each advertisement using the placementsprovided in FIGS. 2A, 2B, and 2C.

TABLE 1 FIG. 2A FIG. 2B FIG. 2C Ad 220 $1.00 $0.70 $0.45 $1.00 (1.0)(0.7) (.45) Ad 221 $0.50 $0.36 $0.90 $0.90 (0.55) (0.4) (1.0) Ad 222$0.24 $0.80 $0.48 $0.80 (0.3) (1.0) (0.6) Total Page EV $1.74 $1.86$1.83

As shown by Table 1, the expected value of each arrangement ofadvertisements differs based on the discount value applied to the ads.As shown by Table 1, the highest expected value is the placement of FIG.2B, which places the smallest advertisement 222 in the first slotdespite that it had the lowest bid. In this example, arranging theadvertisements sequentially by either size or price as shown in FIG. 2Aprovided the lowest expected value. In addition to the arrangementsshown in FIGS. 2A-2C, further arrangements can be evaluated by thesystem to examine the remaining permutations.

In evaluating the placement of advertisements, the system maysequentially view each permutation, or may use optimizations to reducethe number of permutations needed. One optimization is to identifyplacements that are always suboptimal to other placements. For example,provided discount curves which decrease as a function of offset, largerads with an equal or lower value are suboptimal to smaller ads for ahigher slot. A first ad with a large size and a price of $10 will neverbe placed ahead of a second ad with a medium size and a price of $10.This is because for the same or lower price, the medium size ad does notimpact the subsequent ad as much as the larger ad.

Another method for implementing an optimization uses a branch-and-boundtechnique to optimize advertising selection. This technique branchescandidate placements for the first slot and determines bounds on theexpected value for each branch. A maximum value bound is determined toidentify the highest expected value of each branch. To determine maximumvalue bounds for each branch, simplifying assumptions are made for eachbranch. An example simplifying assumption determines or specifies thevalue of placements in slots subsequent to the first slot. Suchsimplifying assumptions may include assigning each slot subsequent tothe first slot the highest discount value for the slot. The branch withthe highest maximum value bound is selected, and an actual placement forthat branch is determined based on possible advertising placements. Thevalue for the actual placement is determined and used to eliminatebranches having a maximum bound lower than the value for the actualplacement. After eliminating branches, the remaining branches areexpanded by creating additional branches for the next most-valuableslot. The maximum value for these branches is determined and the processproceeds to eliminate additional branches. This process continuesrecursively for each slot for the remaining branches until no furtherrecursion is possible and the highest expected value is selected.

In one embodiment, the number of advertising slots is dynamicallyselected depending on the placement results. That is, a pageaccommodates a specific viewing area for containing advertising. Theviewing area may be able to accommodate at most 2 “large” ads, 3“medium” ads, and 4 “small” ads. The advertising selection processidentifies the advertisements which would be selected under eachcircumstance, and identify the EV of the best arrangement of eachmethod. The system can select the number and size of ad which bestmaximizes the expected value of the viewing area.

Advertising Placement Selection

FIG. 3 is a flow chart of a method for selecting ad placements accordingto an embodiment. First, the system receives 300 a request for socialnetworking content from a user. Next, the system identifies 310available advertising slots to accompany the social networking content.The slots are spaces in which the social networking system may serveadvertisements. Based on information about the user and the availableadvertisements, the system determines 320 a set of candidateadvertisements that can be served to the user

The system then determines 330 an expected value for serving selectedones of the candidate advertisements in various placements, where eachplacement includes one of the candidate advertisements in each slot. Theexpected value of a particular placement may be computed as the sum ofthe contributions for each selected ad in the placement. Thecontribution of each ad may be computed based on the bid value of the addiscounted by a factor based on a displacement of the ad and/or the slotin which the ad is placed, as illustrated in FIGS. 2A-2C. For CPCpricing models, the expected value may also be based on an expectedclick-through rate (eCTR). The system may then select 340 a placement ofads (which includes which candidate ads to include in which slots) basedon the determined expected values, such as by selecting the placementwith the highest expected value.

Once the placement order is determined, the advertisements are provided350 to the user along with the social networking content.

Content Types

Though the discount curves above are described relating to the offset ofan advertisement from the top of the page, discount curves may take intoaccount other features of advertisements which affect otheradvertisements in the same advertising space. For example, the contenttype of an advertisement may affect other advertisements in theadvertising space and may be reflected by a discount. Such content typescould include advertisements that include photos, audio, video, textualadvertisements, and other aspects of an advertising campaign. Placing avideo campaign above a textual campaign, for example, may tend toobscure the textual campaign significantly more than the textualcampaign obscures the video campaign.

Advertisements may impact other advertisements in other ways. In oneembodiment, advertisements are associated with a continuationprobability. The continuation probability indicates the likelihood thata user continues to view additional advertisements on the webpage. Forexample, if the advertisements are arranged in a row or a line acrossthe page, the user may scan the advertisements sequentially. Thecontinuation probability indicates the likelihood the user halts viewingadvertisements or whether the user continues to view subsequentadvertisements. The discount of subsequent advertisements is increasedfor advertisements placed after an advertisement likely to cause a userto halt viewing advertisements. However, there may be no discount if anadvertisement with a high likelihood of halting advertisement viewing isplaced last because there are no additional advertisements to view. Thecontinuation probability of an advertisement may be determined by thefrequency that users interact with subsequent advertisements.Alternatively, the continuation probability of an advertisement may beinput by an operator of the system. The operator may view theadvertisement and determine whether the advertisement is likely to causea user to halt advertisement viewing. For example, the operator maydetermine the likelihood of a halt based on objectionable content in theadvertisement. In one embodiment, the social networking system 100automatically determines whether the advertisement containsobjectionable content.

Advertisement Locations

Though described above as impacting an advertising space of offsetswithin a particular portion of the page, the various discount curves mayalso be incorporated into deciding different portions of a page to placeadvertisements. For example the system may have advertising slots on abanner, within main content of the page, or on a sidebar and need tobalance the effects on the advertisers of the various placements. Inaddition, whether to place a particular advertisement within content canbe weighed against the effects on the user of advertising. Suchadvertising may affect user engagement, and the user engagement withcontent can be viewed as a distinct expected value to be improved by thesystem.

Online Content System

Though described above with respect to a social networking system,embodiments of this disclosure include any content system which placesadvertisements in various locations of a user's display. The socialnetworking system may provide ads with different heights because ofsocial content included in the advertisements. Other content systemsinclude variable height (or other dimension) advertisements which impactother advertisements also displayed on the page. These systems may alsouse advertising placement techniques as described herein.

Mixed Content Type Systems

In one embodiment, the selection and bidding process incorporates mixedcontent types. Such content types can include advertisements andrelevant social content for presentation to the user. For example, anadvertisement may be chosen for placement in a feed includinginformation relevant to the user, such as activity by the user'sconnections. Individual pieces of content are selected for placement inthe feed, which may include advertisements and social networkingcontent. The social networking system 100 may determine a monetary valueto the social networking system for providing each piece of content. Forthe advertisements, an expected value of an advertisement to the socialnetworking system 100 is determined. For example, an expected value foran advertisement is determined by multiplying a bid amount associatedwith the advertisement (as provided by an advertiser) by a probabilitythat a user will access the advertisement. As another example, the bidamount of the advertisement is its expected value. For other types ofcontent, a monetary equivalent may be assigned to the piece of contentaccording to the content's relevance to the user, promotion of goalsrelevant to the social networking system, the type of content, and otherfactors. In this embodiment, the selection of content items is selectedby maximizing the monetary value of the content items.

As described above regarding advertisement-only selection, content itemsare selected by optimizing the monetary value of the selected contentitems. The monetary value of content items is also impacted by theplacement of each content item as described above with respect toadvertisements. Accordingly, content item selection may also followcontent selection rules determined by an operator of the socialnetworking system 100. For example, for a mobile device, display spacemay be limited for the user. The content selection rules may thereforedetermine that the first two pieces of content are related to socialnetworking content (e.g., a friend's new photos or a status update) andthat at most one advertisement may be included on the page. Using theserules, the content selection process identifies particular pieces ofcontent for inclusion in the feed to maximize the return to the socialnetworking system. Thus, accounting for the value of providing socialnetworking content as well as advertisements allows the socialnetworking system 100 to obtain maximum value from providing varioustypes of content.

SUMMARY

The foregoing description of the embodiments of the invention has beenpresented for the purpose of illustration; it is not intended to beexhaustive or to limit the invention to the precise forms disclosed.Persons skilled in the relevant art can appreciate that manymodifications and variations are possible in light of the abovedisclosure.

Some portions of this description describe the embodiments of theinvention in terms of algorithms and symbolic representations ofoperations on information. These algorithmic descriptions andrepresentations are commonly used by those skilled in the dataprocessing arts to convey the substance of their work effectively toothers skilled in the art. These operations, while describedfunctionally, computationally, or logically, are understood to beimplemented by computer programs or equivalent electrical circuits,microcode, or the like. Furthermore, it has also proven convenient attimes, to refer to these arrangements of operations as modules, withoutloss of generality. The described operations and their associatedmodules may be embodied in software, firmware, hardware, or anycombinations thereof.

Any of the steps, operations, or processes described herein may beperformed or implemented with one or more hardware or software modules,alone or in combination with other devices. In one embodiment, asoftware module is implemented with a computer program productcomprising a computer-readable medium containing computer program code,which can be executed by a computer processor for performing any or allof the steps, operations, or processes described.

Embodiments of the invention may also relate to an apparatus forperforming the operations herein. This apparatus may be speciallyconstructed for the required purposes, and/or it may comprise ageneral-purpose computing device selectively activated or reconfiguredby a computer program stored in the computer. Such a computer programmay be stored in a non-transitory, tangible computer readable storagemedium, or any type of media suitable for storing electronicinstructions, which may be coupled to a computer system bus.Furthermore, any computing systems referred to in the specification mayinclude a single processor or may be architectures employing multipleprocessor designs for increased computing capability.

Embodiments of the invention may also relate to a product that isproduced by a computing process described herein. Such a product maycomprise information resulting from a computing process, where theinformation is stored on a non-transitory, tangible computer readablestorage medium and may include any embodiment of a computer programproduct or other data combination described herein.

Finally, the language used in the specification has been principallyselected for readability and instructional purposes, and it may not havebeen selected to delineate or circumscribe the inventive subject matter.It is therefore intended that the scope of the invention be limited notby this detailed description, but rather by any claims that issue on anapplication based hereon. Accordingly, the disclosure of the embodimentsof the invention is intended to be illustrative, but not limiting, ofthe scope of the invention, which is set forth in the following claims.

What is claimed is:
 1. A method comprising: receiving a plurality ofadvertising requests, the advertising requests including a bid andadvertising content; identifying an opportunity to provide anadvertisement impression to a viewing user of an online system on aclient device of the viewing user; for the viewing user, identifying adisplay containing an ad space, wherein the ad space is an area of thedisplay having a reference edge and containing a plurality ofadvertising slots arranged along a dimension in the display, thedimension being perpendicular to the reference edge; selecting aplurality of candidate advertisements eligible for display to theviewing user; determining a plurality of candidate placementconfigurations, each placement configuration assigning a candidateadvertisement to each of the plurality of advertising slots in thedisplay; computing a score for each of the candidate placementconfigurations by: determining, for each candidate advertisement, avalue of the candidate advertisement based on the bid for the candidateadvertisement, sending, to the user device, each candidateadvertisement, receiving, from the user device, rendered sizes, in thedimension, for each candidate advertisement, determining, for eachcandidate advertisement, an offset of the candidate advertisement in thedimension from the reference edge based on the candidate placementconfiguration, wherein the offset is a function of the rendered sizes ofcandidate advertisements assigned to advertising slots located betweenthe reference edge and the assigned slot of the candidate advertisement,discounting the determined value of each candidate advertisement basedon the determined offset of the candidate advertisement, wherein anincrease in the size of the determined offset of the candidateadvertisement results in an increased discounting of the candidateadvertisement, and aggregating the discounted values of the plurality ofcandidate advertisements to obtain the score for the candidate placementconfiguration; selecting a candidate placement configuration from theplurality of placement configurations based on the computed scores; andsending, to the client device, the display for viewing by the viewinguser, the display comprising a set of candidate advertisements assignedto the slots according to the selected placement configuration.
 2. Themethod of claim 1, wherein the actual location of the set of candidateadvertisements comprising the display is determined after the display issent to the client device for display.
 3. The method of claim 1, whereinthe rendered sizes of the candidate advertisements are based on theidentity of the viewing user.
 4. The method of claim 1, whereindiscounting the determined value of each candidate advertisement isbased on a discount function, the discount function providing a discountbased on the actual location of each candidate advertisement andestimated user interaction rates with the actual location.
 5. The methodof claim 1, further comprising: determining an amount to charge anadvertiser of a selected advertisement based in part on the bid ofanother selected advertisement.
 6. The method of claim 4, wherein thediscount function is based at least in part on an estimated clickthrough rate for ad placements.
 7. The method of claim 1, wherein theselection of candidate advertisements and the selection of a candidateplacement configuration are based in part on an expected value of theplacement of the selected advertisements relative to an alternativeplacement.
 8. The method of claim 1, wherein discounting the determinedvalue of each candidate advertisement is based in part on which of theadvertising slots each candidate advertisement is assigned.
 9. Themethod of claim 1 further comprising: rendering each of the plurality ofcandidate placement configurations; and determining, for each candidateadvertisement, based on the rendering of each placement configuration,an offset of the candidate advertisement in the dimension from areference position based on the candidate placement configuration andthe size, in the dimension, of the other candidate advertisements. 10.The method of claim 9 further comprising rendering each of the pluralityof candidate placement configurations based on a profile on the onlinesystem of the viewing user.
 11. A method comprising: receiving aplurality of advertising requests, each advertising request including abid; identifying an opportunity to provide an advertisement impressionto a viewing user of an online system on a client device of the viewinguser; for the viewing user, identifying a display containing an adspace, wherein the ad space is an area of the display having a referenceedge and containing a plurality of advertising slots arranged along adimension in the display, the dimension being perpendicular to thereference edge; determining a plurality of candidate advertisements forthe user based on the plurality of advertising requests; for each of aplurality of candidate placements, where a placement comprises aselection of a candidate advertisement from the determinedadvertisements for each advertising slot, computing a value for thecandidate placement that is based on the bids of the advertisements ineach slot and a relative displacement from the reference edge along thedimension of a candidate advertisement in a slot due to an advertisementin another slot, wherein the relative displacement of the candidateadvertisements in each is determined by: sending, to the user device,each candidate advertisement, receiving, from the user device, arendered relative displacement from the reference edge, in thedimension, for each candidate advertisement selecting a placement fromthe candidate placements based on the computed values therefore; andsending the display having the selected placement to the client deviceof the user.
 12. The method of claim 11, wherein each of the pluralityof advertising requests further includes targeting criteria, and theselection of candidate advertisements is based at least in part on thetargeting criteria and a profile associated with the user.
 13. Themethod of claim 11, wherein each of the plurality of the advertisingrequests includes advertising content associated with a size, and therelative displacement of the other selected advertisements is based onthe size of the advertising content in the selection of advertisements.14. The method of claim 13, wherein the size of advertising contentassociated with at least one advertising request in the selection ofadvertisements varies based on the identity of the user.
 15. The methodof claim 14, wherein the size of advertising content is determined inpart on content added to the advertising content.
 16. The method ofclaim 15, wherein the content added to the advertising content is socialnetworking content.
 17. The method of claim 13, wherein the size of theadvertising content is determined based on information received from aclient after the advertising content has been provided to a user.
 18. Amethod comprising: receiving a plurality of advertising requests, eachadvertising request associated with a bid and advertising content; astep for optimizing revenue from a placement configuration of a portionof the advertising content associated with the plurality of advertisingrequests into a plurality of slots arranged along a dimensionperpendicular to a reference edge in an online page of content, theprice of an advertising request based on its bid and an offset in thedimension from a reference edge, wherein the offset is determined by:sending, to the user device, each candidate advertisement, receiving,from the user device, a rendered offset from the reference edge, in thedimension, for each candidate advertisement selecting a placementconfiguration the advertisement content based on the step foroptimizing; and sending the advertising content in the selectedplacement configuration to a user device.